{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>序号</th>\n",
       "      <th>电影名称</th>\n",
       "      <th>搞笑镜头</th>\n",
       "      <th>拥抱镜头</th>\n",
       "      <th>打斗镜头</th>\n",
       "      <th>电影类型</th>\n",
       "      <th>唐人街探案</th>\n",
       "      <th>23</th>\n",
       "      <th>3</th>\n",
       "      <th>17</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>宝贝当家</td>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>喜剧片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>美人鱼</td>\n",
       "      <td>21</td>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>喜剧片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>澳门风云3</td>\n",
       "      <td>54</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>喜剧片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>功夫熊猫3</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>喜剧片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>谍影重重</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>57</td>\n",
       "      <td>动作片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>叶问3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>65</td>\n",
       "      <td>动作片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>我的特工爷爷</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>动作片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>奔爱</td>\n",
       "      <td>7</td>\n",
       "      <td>46</td>\n",
       "      <td>4</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>夜孔雀</td>\n",
       "      <td>9</td>\n",
       "      <td>39</td>\n",
       "      <td>8</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>代理情人</td>\n",
       "      <td>9</td>\n",
       "      <td>38</td>\n",
       "      <td>2</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>新步步惊心</td>\n",
       "      <td>8</td>\n",
       "      <td>34</td>\n",
       "      <td>17</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>伦敦陷落</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>动作片</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    序号    电影名称  搞笑镜头  拥抱镜头  打斗镜头 电影类型  唐人街探案  23   3  17\n",
       "0    1    宝贝当家    45     2     9  喜剧片    NaN NaN NaN NaN\n",
       "1    2     美人鱼    21    17     5  喜剧片    NaN NaN NaN NaN\n",
       "2    3   澳门风云3    54     9    11  喜剧片    NaN NaN NaN NaN\n",
       "3    4   功夫熊猫3    39     0    31  喜剧片    NaN NaN NaN NaN\n",
       "4    5    谍影重重     5     2    57  动作片    NaN NaN NaN NaN\n",
       "5    6     叶问3     3     2    65  动作片    NaN NaN NaN NaN\n",
       "6    7  我的特工爷爷     6     4    21  动作片    NaN NaN NaN NaN\n",
       "7    8      奔爱     7    46     4  爱情片    NaN NaN NaN NaN\n",
       "8    9     夜孔雀     9    39     8  爱情片    NaN NaN NaN NaN\n",
       "9   10    代理情人     9    38     2  爱情片    NaN NaN NaN NaN\n",
       "10  11   新步步惊心     8    34    17  爱情片    NaN NaN NaN NaN\n",
       "11  12    伦敦陷落     2     3    55  动作片    NaN NaN NaN NaN"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_excel(\"电影分类数据.xlsx\")\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>爱情片</td>\n",
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       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>39</td>\n",
       "      <td>8</td>\n",
       "      <td>爱情片</td>\n",
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       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>38</td>\n",
       "      <td>2</td>\n",
       "      <td>爱情片</td>\n",
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       "      <th>10</th>\n",
       "      <td>8</td>\n",
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       "      <td>17</td>\n",
       "      <td>爱情片</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>动作片</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    搞笑镜头  拥抱镜头  打斗镜头 电影类型\n",
       "0     45     2     9  喜剧片\n",
       "1     21    17     5  喜剧片\n",
       "2     54     9    11  喜剧片\n",
       "3     39     0    31  喜剧片\n",
       "4      5     2    57  动作片\n",
       "5      3     2    65  动作片\n",
       "6      6     4    21  动作片\n",
       "7      7    46     4  爱情片\n",
       "8      9    39     8  爱情片\n",
       "9      9    38     2  爱情片\n",
       "10     8    34    17  爱情片\n",
       "11     2     3    55  动作片"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 所有的训练集【特征和标签】\n",
    "train_data = data.loc[:, \"搞笑镜头\":\"电影类型\"]\n",
    "train_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([23, 3, 17], dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 测试样本\n",
    "test_sample = data.columns[-3:]\n",
    "test_sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>38</td>\n",
       "      <td>2</td>\n",
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       "      <th>10</th>\n",
       "      <td>8</td>\n",
       "      <td>34</td>\n",
       "      <td>17</td>\n",
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       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    搞笑镜头  拥抱镜头  打斗镜头\n",
       "0     45     2     9\n",
       "1     21    17     5\n",
       "2     54     9    11\n",
       "3     39     0    31\n",
       "4      5     2    57\n",
       "5      3     2    65\n",
       "6      6     4    21\n",
       "7      7    46     4\n",
       "8      9    39     8\n",
       "9      9    38     2\n",
       "10     8    34    17\n",
       "11     2     3    55"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 训练集的特征\n",
    "trian_X = train_data.iloc[:,:-1]\n",
    "trian_X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     23.430749\n",
       "1     18.547237\n",
       "2     32.140317\n",
       "3     21.470911\n",
       "4     43.874822\n",
       "5     52.009614\n",
       "6     17.492856\n",
       "7     47.686476\n",
       "8     39.661064\n",
       "9     40.570926\n",
       "10    34.438351\n",
       "11    43.416587\n",
       "dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 广播机制 （12,3）  （3，）\n",
    "dis = np.sqrt(((trian_X-test_sample)**2).sum(axis=1))\n",
    "dis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>3</th>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>喜剧片</td>\n",
       "      <td>21.470911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>喜剧片</td>\n",
       "      <td>23.430749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>54</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>喜剧片</td>\n",
       "      <td>32.140317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8</td>\n",
       "      <td>34</td>\n",
       "      <td>17</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>34.438351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>39</td>\n",
       "      <td>8</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>39.661064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>38</td>\n",
       "      <td>2</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>40.570926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>55</td>\n",
       "      <td>动作片</td>\n",
       "      <td>43.416587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>57</td>\n",
       "      <td>动作片</td>\n",
       "      <td>43.874822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>46</td>\n",
       "      <td>4</td>\n",
       "      <td>爱情片</td>\n",
       "      <td>47.686476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>65</td>\n",
       "      <td>动作片</td>\n",
       "      <td>52.009614</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    搞笑镜头  拥抱镜头  打斗镜头 电影类型         距离\n",
       "6      6     4    21  动作片  17.492856\n",
       "1     21    17     5  喜剧片  18.547237\n",
       "3     39     0    31  喜剧片  21.470911\n",
       "0     45     2     9  喜剧片  23.430749\n",
       "2     54     9    11  喜剧片  32.140317\n",
       "10     8    34    17  爱情片  34.438351\n",
       "8      9    39     8  爱情片  39.661064\n",
       "9      9    38     2  爱情片  40.570926\n",
       "11     2     3    55  动作片  43.416587\n",
       "4      5     2    57  动作片  43.874822\n",
       "7      7    46     4  爱情片  47.686476\n",
       "5      3     2    65  动作片  52.009614"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data[\"距离\"] = dis\n",
    "\n",
    "# 按照距离排序---【从小到大】\n",
    "train_data.sort_values(by=\"距离\", ascending=True, inplace=True)\n",
    "train_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "唐人街探案类型: 喜剧片\n"
     ]
    }
   ],
   "source": [
    "K=5\n",
    "\n",
    "# print(\"选择前5个\\n\", train_data.head(K))\n",
    "\n",
    "# 众数返回结果是Series\n",
    "print(\"唐人街探案类型:\", train_data.head(K)[\"电影类型\"].mode()[0])"
   ]
  }
 ],
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